What is Transfer Learning? Transfer Learning in Keras | Fine Tuning Vs Feature Extraction

Transfer learning is a research problem in machine learning that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem. For example, knowledge gained while learning to recognize cars could apply when trying to recognize trucks.

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⌚Time Stamps⌚

00:00 - Intro
00:50 - problem with training your own model
02:35 - Using Pre-trained Model
07:01 - Using Transfer Learning
13:54 - Why Transfer Learning Works?
17:41 - Ways of doing Transfer Learning
20:54 - Code Example using KERAS

[Jannatkhan-vznj]

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[himanshumangoli]

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Thanks brother

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[hammadfaheem]

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[yibenthung]

I just love the way you simplified the concepts like transfer learning, fine tuning, and the architecture of the CNNs. Thank you bhaiya🙏

[abhikantbhave]

Thanks Nitish. this video is superb.

if anyone is getting the error, import these libraries. (keras library is changed for load_img and img_to_array
from keras.utils import img_to_array, load_img
from keras.applications.vgg16 import preprocess_input
from numpy import expand_dims

also use "keras.Model" instead of only "Model" to get the layers,
use this --> model = keras.Model (inputs=model.inputs, outputs=model.layers[1].output)
instead of -->model = Model (inputs=model.inputs, outputs=model.layers[1].output)

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[rb]

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